Data Engineer

Thai Insurance Research and Development Co., Ltd. (TIRD)

• Phra Khanong, Bangkok
• Reports to Head of Enterprise Data Solutions

Help Build the Future of Insurance Data in Thailand!!!

Are you a problem solver who loves working with data? Do you enjoy fixing messy systems, improving performance, and building new data platforms from the ground up?

We're looking for a Data Engineer who's ready to roll up their sleeves and tackle real-world challenges - from messy pipelines and performance bottlenecks to cloud modernization and data governance.

Key Responsibilities

Design, develop, and maintain robust data pipelines using Apache Airflow, SSIS, PySpark, and Talend to ingest, transform, and load large-scale datasets (300M+ rows) from multiple sources.

• Manage and optimize relational databases including Oracle and SQL Server, ensuring high performance and scalability for analytical workloads.

• Design, build, and maintain cloud data platforms and warehousing solutions using AWS services such as Redshift and S3, alongside ClickHouse for high-performance analytical querying.

• Develop and maintain OLAP solutions using SSAS for advanced reporting and analytics, including cube design, partitioning, and aggregation strategies.

• Implement ETL processes for structured and semi-structured data, ensuring data quality, consistency, and compliance with industry standards.

• Collaborate with the BI Team, Actuarial Team, and business stakeholders to understand requirements and deliver efficient data models and solutions.

• Monitor and improve data pipeline performance, troubleshoot bottlenecks, and implement best practices for parallel processing and resource optimization.

• Ensure data security and compliance with insurance industry regulations and company policies.

• Leverage big data technologies such as Apache Spark for distributed processing and advanced data transformations.

• Automate workflows and scheduling using Airflow DAGs, ensuring reliability and scalability of data operations.

• Document data architecture, processes, and standards, and provide technical guidance to team members.

Required

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field.

• 3-5 years of experience building and maintaining data pipelines.

• Proficiency in SQL and experience with relational databases (Oracle, SQL Server), including performance tuning and query optimization.

• Hands-on experience with ETL tools such as SSIS, Talend, and PySpark, and data modeling for OLAP solutions using SSAS.

• Knowledge of data pipeline orchestration using Apache Airflow.

• Experience with big data processing frameworks such as Apache Spark for distributed data transformations.

• Hands-on experience with cloud database/data platform services such as AWS Redshift, S3, and ClickHouse.

• Solid understanding of data warehousing concepts, star/snowflake schema, and partitioning strategies for large datasets (300M+ rows).

• Proficiency in Python or another scripting language for automation and data manipulation.

• Knowledge of data quality, governance, and security best practices.

• Ability to work with large-scale data and optimize workflows for performance and scalability.

• Familiarity with insurance industry data or other regulated environments is a plus.

Preferred

Qualifications

Experience with Power BI and building efficient data marts.

• Experience with data privacy, governance, and secure data access practices.

• Hands-on with additional cloud platforms/tools such as Azure, Databricks, Delta Lake, Snowflake, or the Hadoop ecosystem.

• Able to troubleshoot performance issues in both backend pipelines and frontend analytics tools.

• Comfortable working in a fast-paced, high-ownership environment with cross-functional teams.

Why Join Us

• Build Thailand's insurance data infrastructure from the ground up - real ownership over pipelines and platforms that power an entire industry, not just one company.

• Work with a modern, varied tech stack (Airflow, Spark, AWS, ClickHouse) and real scale (300M+ row datasets), with room to modernize legacy systems your way.

• Close collaboration with BI and Actuarial teams gives you direct visibility into how your data work drives business and industry decisions.